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Record W3033178325 · doi:10.1002/fsh.10488

Has Steller Sea Lion Predation Impacted Survival of Fraser River Sockeye Salmon?

2020· article· en· W3033178325 on OpenAlexafffundabout
Carl J. Walters, Murdoch K. McAllister, Villy Christensen

Bibliographic record

VenueFisheries · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaPacific Salmon Foundation
KeywordsPredationFisheryGeographySea lionBiologyEcology

Abstract

fetched live from OpenAlex

Abstract The commercially, recreationally, and culturally important Fraser River Sockeye Salmon Oncorhynchus nerka has experienced a productivity decline over the past 3 decades, which—along with greater temporal variation in annual abundance (i.e., cyclic dominance)—may at least partly be due to Steller sea lion Eumetopias jubatus (SSL) predation on returning adult salmon. This assumes that SSLs residing around northern Vancouver Island (British Columbia, Canada) target Sockeye Salmon for just a few weeks during the peak of their run. It is a reasonable enough assumption to warrant immediate priority for field research on SSL behavior and diets during the migration period. We evaluated the plausibility of the assumption with a variety of approaches ranging from simple estimates of maximum SSL consumption to partitioning of observed marine mortality rates and analysis of SSL foraging behavior to show that SSLs could have caused the decline in productivity and abundance of Fraser River Sockeye Salmon.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.212
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2020
Admission routes3
Has abstractyes

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